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comparison infer_experiment.xml @ 49:6b33e31bda10 draft

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Uploaded tar based on https://github.com/lparsons/galaxy_tools/tree/master/tools/rseqc 1a3c419bc0ded7c40cb2bc3e7c87bfb01ddfeba2
author lparsons
date Thu, 16 Jul 2015 17:43:43 -0400
parents eb339c5849bb
children 09846d5169fa
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48:2e6190c29c54 49:6b33e31bda10
1 <tool id="rseqc_infer_experiment" name="Infer Experiment" version="2.4"> 1 <tool id="rseqc_infer_experiment" name="Infer Experiment" version="2.4galaxy1">
2 <description>speculates how RNA-seq were configured</description> 2 <description>speculates how RNA-seq were configured</description>
3
4 <macros>
5 <import>rseqc_macros.xml</import>
6 </macros>
7
3 <requirements> 8 <requirements>
4 <requirement type="package" version="1.7.1">numpy</requirement> 9 <expand macro="requirement_package_numpy" />
5 <requirement type="package" version="2.4">rseqc</requirement> 10 <expand macro="requirement_package_rseqc" />
6 </requirements> 11 </requirements>
7 <command>
8 infer_experiment.py -i $input -r $refgene
9 #if $sample_size.boolean
10 -s $sample_size.size
11 #end if
12 12
13 <expand macro="stdio" />
14
15 <version_command><![CDATA[infer_experiment.py --version]]></version_command>
16
17 <command><![CDATA[
18 infer_experiment.py -i $input -r $refgene
19 --sample-size $sample_size
20 --mapq $mapq
13 > $output 21 > $output
22 ]]>
14 </command> 23 </command>
15 <stdio> 24
16 <exit_code range="1:" level="fatal" description="An error occured during execution, see stderr and stdout for more information" />
17 <regex match="[Ee]rror" source="both" description="An error occured during execution, see stderr and stdout for more information" />
18 </stdio>
19 <inputs> 25 <inputs>
20 <param name="input" type="data" format="bam,sam" label="Input BAM/SAM file" /> 26 <param name="input" type="data" format="bam,sam" label="Input BAM/SAM file" help="(--input-file)"/>
21 <param name="refgene" type="data" format="bed" label="Reference gene model in bed format" /> 27 <param name="refgene" type="data" format="bed" label="Reference gene model in bed format" help="(--refgene)" />
22 <conditional name="sample_size"> 28 <param name="sample_size" type="integer" label="Number of reads sampled from SAM/BAM file (default = 200000)" value="200000" help="(--sample-size)"/>
23 <param name="boolean" type="boolean" label="Modify usable sampled reads" value="false" /> 29 <param name="mapq" type="integer" label="Minimum mapping quality (default=30)" help="Minimum phred scale mapping quality to consider a read 'uniquely mapped' (--mapq)" value="30" />
24 <when value="true">
25 <param name="size" type="integer" label="Number of usable sampled reads (default = 200000)" value="200000" />
26 </when>
27 </conditional>
28 </inputs> 30 </inputs>
31
29 <outputs> 32 <outputs>
30 <data format="txt" name="output" /> 33 <data format="txt" name="output" />
31 </outputs> 34 </outputs>
32 <help> 35
36 <tests>
37 <test>
38 <param name="input" value="pairend_strandspecific_51mer_hg19_chr1_1-100000.bam"/>
39 <param name="refgene" value="hg19_RefSeq_chr1_1-100000.bed"/>
40 <output name="output" file="output.infer_experiment.txt"/>
41 </test>
42 </tests>
43
44 <help><![CDATA[
33 infer_experiment.py 45 infer_experiment.py
34 +++++++++++++++++++ 46 +++++++++++++++++++
35 47
36 This program is used to speculate how RNA-seq sequencing were configured, especially how 48 This program is used to speculate how RNA-seq sequencing were configured, especially how
37 reads were stranded for strand-specific RNA-seq data, through comparing reads' mapping 49 reads were stranded for strand-specific RNA-seq data, through comparing reads' mapping
38 information to the underneath gene model. 50 information to the underneath gene model.
39 51
40 52
41 Inputs 53 Inputs
42 ++++++++++++++ 54 ++++++++++++++
43 55
99 *Conclusion*: We can infer that this is NOT a strand specific because 50% of reads can be explained by "1++,1--,2+-,2-+", while the other 50% can be explained by "1+-,1-+,2++,2--". 111 *Conclusion*: We can infer that this is NOT a strand specific because 50% of reads can be explained by "1++,1--,2+-,2-+", while the other 50% can be explained by "1+-,1-+,2++,2--".
100 112
101 **Example2** :: 113 **Example2** ::
102 114
103 ============================================================ 115 ============================================================
104 This is PairEnd Data 116 This is PairEnd Data
105 117
106 Fraction of reads explained by "1++,1--,2+-,2-+": 0.9644 :: 118 Fraction of reads explained by "1++,1--,2+-,2-+": 0.9644 ::
107 Fraction of reads explained by "1+-,1-+,2++,2--": 0.0356 119 Fraction of reads explained by "1+-,1-+,2++,2--": 0.0356
108 Fraction of reads explained by other combinations: 0.0000 120 Fraction of reads explained by other combinations: 0.0000
109 ============================================================ 121 ============================================================
110 122
111 *Conclusion*: We can infer that this is a strand-specific RNA-seq data. strandness of read1 is consistent with that of gene model, while strandness of read2 is opposite to the strand of reference gene model. 123 *Conclusion*: We can infer that this is a strand-specific RNA-seq data. strandness of read1 is consistent with that of gene model, while strandness of read2 is opposite to the strand of reference gene model.
112 124
113 **Example3** :: 125 **Example3** ::
114 126
115 ========================================================= 127 =========================================================
123 *Conclusion*: This is single-end, strand specific RNA-seq data. Strandness of reads are concordant with strandness of reference gene. 135 *Conclusion*: This is single-end, strand specific RNA-seq data. Strandness of reads are concordant with strandness of reference gene.
124 136
125 137
126 ----- 138 -----
127 139
128 About RSeQC 140 About RSeQC
129 +++++++++++ 141 +++++++++++
130 142
131 The RSeQC_ package provides a number of useful modules that can comprehensively evaluate high throughput sequence data especially RNA-seq data. "Basic modules" quickly inspect sequence quality, nucleotide composition bias, PCR bias and GC bias, while "RNA-seq specific modules" investigate sequencing saturation status of both splicing junction detection and expression estimation, mapped reads clipping profile, mapped reads distribution, coverage uniformity over gene body, reproducibility, strand specificity and splice junction annotation. 143 The RSeQC_ package provides a number of useful modules that can comprehensively evaluate high throughput sequence data especially RNA-seq data. "Basic modules" quickly inspect sequence quality, nucleotide composition bias, PCR bias and GC bias, while "RNA-seq specific modules" investigate sequencing saturation status of both splicing junction detection and expression estimation, mapped reads clipping profile, mapped reads distribution, coverage uniformity over gene body, reproducibility, strand specificity and splice junction annotation.
132 144
133 The RSeQC package is licensed under the GNU GPL v3 license. 145 The RSeQC package is licensed under the GNU GPL v3 license.
134 146
135 .. image:: http://rseqc.sourceforge.net/_static/logo.png 147 .. image:: http://rseqc.sourceforge.net/_static/logo.png
136 148
137 .. _RSeQC: http://rseqc.sourceforge.net/ 149 .. _RSeQC: http://rseqc.sourceforge.net/
138 150
151 ]]>
152 </help>
139 153
140 </help> 154 <expand macro="citations" />
155
141 </tool> 156 </tool>